With the rapid development of electronics and the growing demand for highervehicle performance, intelligent shift technology is becoming increasingly important, and itpromises to be a developing trend in vehicle autom...With the rapid development of electronics and the growing demand for highervehicle performance, intelligent shift technology is becoming increasingly important, and itpromises to be a developing trend in vehicle automatic transmissions, A new simulation model ispresented, which includes engine, powertrain, tire and vehicle dynamics models. Based on the model,simulation experiments are conducted to investigate the slope shift strategy. The data andconclusions obtained from the simulations are valuable contributions to the development of anintelligent slope shift strategy.展开更多
The shift scheduling system of the transmission has an important effect on the dynamic and economic performance of hybrid vehicles. In this work, shift scheduling strategies are developed for parallel hybrid construct...The shift scheduling system of the transmission has an important effect on the dynamic and economic performance of hybrid vehicles. In this work, shift scheduling strategies are developed for parallel hybrid construction vehicles. The effect of power distribution and direction on shift characteristics of the parallel hybrid vehicle with operating loads is evaluated, which must be considered for optimal shift control. A power distribution factor is defined to accurately describe the power distribution and direction in various parallel hybrid systems. This paper proposes a Levenberg-Marquardt algorithm optimized neural network shift scheduling strategy. The methodology contains two objective functions, it is a dynamic combination of a dynamic shift schedule for optimal vehicle acceleration, and an energy-efficient shift schedule for optimal powertrain efficiency. The study is performed on a test bench under typical operating conditions of a wheel loader. The experimental results show that the proposed strategies offer effective and competitive shift performance.展开更多
基金This project is supported by Important Scientech Problem Tackling Subject Foundation under the State 9th 5-Year Plan, China(No.96-A05-04-01).
文摘With the rapid development of electronics and the growing demand for highervehicle performance, intelligent shift technology is becoming increasingly important, and itpromises to be a developing trend in vehicle automatic transmissions, A new simulation model ispresented, which includes engine, powertrain, tire and vehicle dynamics models. Based on the model,simulation experiments are conducted to investigate the slope shift strategy. The data andconclusions obtained from the simulations are valuable contributions to the development of anintelligent slope shift strategy.
基金Project(51805200)supported by the National Natural Science Foundation of ChinaProject(20170520096JH)supported by the Science and Technology Development Plan of Jilin Province,ChinaProject(2016YFC0802900)supported by the National Key R&D Program of China
文摘The shift scheduling system of the transmission has an important effect on the dynamic and economic performance of hybrid vehicles. In this work, shift scheduling strategies are developed for parallel hybrid construction vehicles. The effect of power distribution and direction on shift characteristics of the parallel hybrid vehicle with operating loads is evaluated, which must be considered for optimal shift control. A power distribution factor is defined to accurately describe the power distribution and direction in various parallel hybrid systems. This paper proposes a Levenberg-Marquardt algorithm optimized neural network shift scheduling strategy. The methodology contains two objective functions, it is a dynamic combination of a dynamic shift schedule for optimal vehicle acceleration, and an energy-efficient shift schedule for optimal powertrain efficiency. The study is performed on a test bench under typical operating conditions of a wheel loader. The experimental results show that the proposed strategies offer effective and competitive shift performance.
